"""simple docstring"""



from dataclasses import dataclass
from typing import List, Optional, Union

import numpy as np
import PIL

from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available
from .timesteps import (
    fastaa_timesteps,
    smartaa_timesteps,
    smartaa_timesteps,
    smartaaa_timesteps,
    smartaaa_timesteps,
    superaa_timesteps,
    superaa_timesteps,
    superaaa_timesteps,
)






@dataclass
class  snake_case__      (       snake_case_       ):
 _snake_case       :					Union[List[PIL.Image.Image], np.ndarray]
 _snake_case       :					Optional[List[bool]]
 _snake_case       :					Optional[List[bool]]


try:
   if not (is_transformers_available() and is_torch_available()):
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   from ...utils.dummy_torch_and_transformers_objects import *  # noqa F403
else:
   from .pipeline_if import IFPipeline
   from .pipeline_if_imgaimg import IFImgaImgPipeline
   from .pipeline_if_imgaimg_superresolution import IFImgaImgSuperResolutionPipeline
   from .pipeline_if_inpainting import IFInpaintingPipeline
   from .pipeline_if_inpainting_superresolution import IFInpaintingSuperResolutionPipeline
   from .pipeline_if_superresolution import IFSuperResolutionPipeline
   from .safety_checker import IFSafetyChecker
   from .watermark import IFWatermarker

"""simple docstring"""



import warnings

from ...utils import logging
from .image_processing_donut import DonutImageProcessor


SCREAMING_SNAKE_CASE__:Dict									=			logging.get_logger(__name__)






class  snake_case__      (       snake_case_       ):


 def __init__( self    ,		*lowerCamelCase    ,		**lowerCamelCase						):
        warnings.warn(
            "The class DonutFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please"
            " use DonutImageProcessor instead."    ,		lowerCamelCase    ,		)
        super().__init__(*lowerCamelCase    ,		**lowerCamelCase						)
